Beauty and the Beast: Optimal Methods Meet Learning for Drone Racing

Understand

Autonomous micro aerial vehicles still struggle with fast and agile maneuvers, dynamic environments, imperfect sensing, and state estimation drift.

• Autonomous drone racing brings these challenges to the fore.
• Human pilots can fly a previously unseen track after a handful of practice runs.
• In contrast, state-of-the-art autonomous navigation algorithms require either a precise metric map of the environment or a large amount of training data collected in the track of interest.